David Richardson Page 1 2/28/2005 

Should NIOSH adopt the NIH-IREP model for lung cancer for use in the 

EEOICPA?

The National Cancer Institute revised the NIH-IREP lung cancer model in late 2003 in 

response to a report on analyses of the joint effects of radiation and cigarette smoking on 

lung cancer risk among the Japanese atomic bomb survivors (Pierce, Sharp et al. 2003). 

The IREP model allows for interaction on the relative rate scale between radiation dose 

and cigarette smoking with an uncertainty distribution for an “adjustment factor” that 

accommodates an additive, multiplicative, or super-multiplicative interaction (Apostoaei 

and Trabalka 2004). Under the revised NIH-IREP lung model the distribution for this 

adjustment factor is more heavily weighted toward an additive interaction between 

radiation dose and cigarette smoking than under the NIOSH-IREP model. Consequently, 

the same inputs entered into NIH-IREP and NIOSH-IREP produce significantly different 

probabilities of causation for some exposure profiles. Apostoaei and Trabalka recently 

recommended that NIOSH adopt the NIH-IREP model for lung cancer (Apostoaei and 

Trabalka 2004). 

Statistical and Biological Models for Interaction 

NIOSH is concerned with appropriately characterizing the interaction on a relative rate 

scale between two time-varying continuous exposure variables (i.e., occupational 

radiation doses and cigarette smoking rates). In contrast to the statistical evaluation of 

product terms for two fixed binary exposure variables, an evaluation of the interaction 

between smoking history and occupational radiation exposure history may be relatively 

complex. Statistical evidence of a smoking-radiation dose interaction may depend upon 

model assumptions about the etiologically-relevant periods of exposure for each agent, 

assumptions about the importance of the temporal ordering of exposures, and 

assumptions about the shapes of the exposure-response patterns for single versus joint 

exposures. Misspecification of such assumptions may lead to incorrect conclusions about 

the nature of the interaction between exposures. 

Multistage models of carcinogenesis provide a useful starting point for discussion of joint 

exposures in lung carcinogenesis. One consideration is the importance of the temporal 

pattern of exposures on the magnitude of the joint effects of exposure. For some 

carcinogens the temporal ordering of exposures and the time interval between exposures 

is an important determinant of the magnitude of their joint effects. If exposure to 

cigarette smoke leads to a change in the probability of an early stage event in a multistage 

process of carcinogenesis then accrual of cigarette smoke exposures late in life (and 

specifically after radiation exposure from the A-bomb) may have a relative small impact 

on lung cancer risk. In contrast, exposure to cigarette smoke early in life (and 

particularly prior to radiation exposure from the A-bomb) may have a relatively large 

impact on lung cancer risk. 

Multistage models of carcinogenesis further suggest that the temporal pattern of 

exposures may impact the distribution of induction/latency periods for lung cancer (as 

well as the subsequent evolution of risk patterns over time). It is plausible that early 
David Richardson Page 2 2/28/2005 

cigarette smoke exposure(s) may influence later susceptibility to radiation risk and that 

this association may differ in magnitude and temporality from that observed when 

radiation dose precedes cigarette smoking. One might postulate, for example, that 

radiation-induced lung cancer may tend to appear after shorter induction/latency periods 

for people who were smokers than non-smokers (Archer, Coons et al. 2004). Classical 

multistage models of carcinogenesis, and contemporary understanding of the molecular 

basis of lung cancer pathology suggest that the distribution of induction/latency periods 

for lung cancer may differ for those with single versus joint exposure to these agents (and 

that the distribution may vary in relation to the temporal order of exposure, and the time 

interval between exposures). Of course either exposure may influence more than one 

stage of a multistage disease process; however, regardless of whether an exposure 

influences one or more stages of this process, its relative influence on the change in the 

probability of each event may differ due to baseline rates for these events so that such a 

carcinogen’s impact may primarily act at an early or late stage. 

Joint effects of radiation and smoking among Japanese A-bomb survivors 

The situation considered by Pierce, et al. is somewhat simpler than that of direct concern 

to NIOSH since in the case of the study of atomic bomb survivors radiation dose is 

considered as a fixed variable. Pierce et al. investigated lung cancer incidence using 

information for a subcohort of the Lifespan Study (LSS) of atomic bomb survivors that 

includes approximately 45,000 survivors for whom smoking history information was 

available and for whom cancer incidence was determined through 1994 (Pierce, Sharp et 

al. 2003). 

In their analysis Pierce et al. further simplified their investigation of the interaction 

between cigarette smoking and radiation dose by treating cigarette smoking as a fixed 

(rather than time-dependent) variable. Subjects were treated as continuous smokers (at a 

fixed rate based upon the response to at least one survey about cigarette smoking) or 

never smokers. They do not consider age at start of smoking or its relation to age at time 

of bombing; they do not consider age at termination of smoking or its relation to age at 

onset of cancer; and, they do not consider the duration of smoking or cumulative packyears. 

Their cited reasons for this simplification included the analytical difficulties of utilizing 

information on each person’s smoking history and the limitations of the available 

smoking history data. A fundamental question, however, is whether the investigators’ 

simplified approach to treating the temporal aspects of joint exposures have led to 

spurious conclusions about the true nature of the joint effects of these agents. 

Mechanistic models and experimental evidence for some carcinogen pairs suggest that 

the temporal patterns of exposures and subsequent disease risk are fundamental 

considerations when trying to appropriately characterize the joint effects of the 

exposures. In such cases failing to consider the temporal aspects of the interaction may 

lead one to draw spurious conclusions about the nature of the interaction between these 

agents and the consistency of the interaction effect over time. In the case of cigarette 

smoking, prior epidemiological research has established that the temporal aspects of 
David Richardson Page 3 2/28/2005 

smoking history are important considerations when evaluating smoking effects on lung 

cancer risk (Brown and Chu 1987; Doll, Peto et al. 2004). It is reasonable to postulate 

that the temporal aspects of smoking history may be as important or more important to 

analyses of the joint effects of smoking and radiation dose on lung cancer risk. 

As Pierce et al. note, one reason for their simplified approach to constructing an exposure 

metric from individual smoking histories was the limitations in the available data. A 

number of authors have discussed limitations in the LSS study as they relate to analyses 

of radiation-cancer mortality associations. These include concerns about health-related 

selection processes, incomplete and inaccurate reporting on location at time of bombing 

(survivor), and other uncertainties about prompt and residual radiation exposure estimates 

(Shimizu, Kato et al. 1992; Stewart and Kneale 1998). 

In addition to these considerations the study question investigated by Pierce et al. requires 

relatively complete and valid information on individual survivor’s smoking histories. In 

order to fully characterize the nature of the interaction between smoking and radiation 

dose the study requires complete smoking histories that span the period prior to the 

nuclear attack until the end of follow-up for each survivor. The survey data used in this 

analysis, in contrast, provides snapshots in time of smoking histories for those who 

responded to mail questionnaires or clinic visits. Such information is highly incomplete 

(missing entirely for about 45% of survivors); for those with some information on 

smoking history, information analyzed on smoking rate pertains to the average smoking 

rate reported at one or more survey dates. No information in these analyses characterizes 

the potential variation in smoking rates over decades of life prior to the atomic bombing 

or, in fact, prior to first survey in the 1960s. 

As in any epidemiological analysis based on self-reported information it is reasonable to 

question the reliability of this information. Such considerations are particularly important 

given the context of a research program initiated by an occupying military of a population 

of atomic bomb survivors. The authors state that about 2400 (i.e, roughly 5%) of those 

who responded to at least one mail or clinical survey provided incomplete or inconsistent 

information and had to be excluded from analyses. It is likely that other survivors 

provided information that was inaccurate but not logically inconsistent and therefore was 

included in these analyses. 

Crucially, the analyses reported by Pierce et al. are constrained to provide information on 

the nature of the smoking-radiation dose interaction only for the period that begins 

approximately two decades after radiation exposure. Pierce et al. note that “there is 

something lost by the later-than-usual entry to follow-up” (Pierce, Sharp et al. 2003). 

Specifically what is lost is the ability to characterize the nature of radiation-induced lung 

cancer during the first roughly 19 years after exposure; further, while the joint effects of 

radiation and smoking exposure are of interest, these analyses do not evaluate their joint 

effects during this extended period (nearly two decades) after radiation exposure. This is 

another limitation that relates to the absence of complete smoking history information for 

A-bomb survivors. A person only enters follow-up on the date that smoking history 

information was first obtained. Consequently, while the pattern of lung cancer risk 
David Richardson Page 4 2/28/2005 

during the years (and decades) immediately after radiation exposure is potentially very 

important to the characterization of the joint effects of smoking and radiation dose, this 

period of observation is not captured by these analyses. As Pierce et al. note, information 

on smoking was obtained in several mail surveys and clinical interviews between 1964 

and 1992. Therefore people do not enter follow-up until 1964 or later and consequently 

(in contrast to most analyses of LSS data) lung cancer risk during the first 19 years after 

exposure to ionizing radiation is not incorporated into the analysis of the joint effects of 

smoking and radiation. Many females did not enter follow-up until approximately 25 

years after radiation exposure (when the first mail survey that included females was 

conducted) which is important since two-thirds of the study subjects in this analysis are 

female. Evaluation of the joint effects of smoking and radiation on lung cancer risk is 

therefore constrained by the inability to evaluate, for example, a prompt peak in lung 

cancer risk following ionizing radiation exposure among smokers. If the joint effects of 

radiation and smoking exposures on lung cancer risk were relatively largest in these early 

years after radiation exposure, and diminished with protracted time since exposure, then 

the analysis by Pierce would mischaracterize their joint effects due to the limitation of 

only examining later periods of follow-up. 

The requirement that persons be alive and cancer-free at the time of the smoking surveys 

also has implications for evaluations of variation in ERR/Sv with age-at-exposure. As 

illustrated in Figure 3 of the paper by Pierce et al.(2003) a relatively small number of Abomb survivors who were aged 50 or older at time of bombing were eligible for inclusion 

in this analysis; and a substantial proportion of these survivors would be classified in the 

lowest (i.e. referent) radiation dose category (Pierce, Sharp et al. 2003). Figure 3 does 

not show the number of lung cancer cases among those aged 50+ at time of bombing but 

presumably a very small number of lung cancer cases were available for analyses of 

radiation dose-lung cancer associations among those exposed to radiation (above the 

referent level) at older adult ages. Prior analyses of the full LSS cohort found that the 

ERR/Sv for lung cancer was larger for those exposed at older adult ages (e.g., age 50+) 

than at younger adult ages (Pierce, Shimizu et al. 1996). Pierce et al., in contrast, note 

that in these analyses there is no statistically significant age-at-exposure effect for lung 

cancer when allowing the ERR/Sv to decrease with attained age (Pierce, Sharp et al. 

2003). This conclusion, however, needs to be tempered by the fact that their recent 

analysis has very little ability to evaluate radiation effects on lung cancer risk among 

those survivors exposed to radiation at older adult ages since only a very small number of 

survivors (and in particular lung cancer cases) were observed among survivors who were 

exposed at older adult ages. Furthermore, conclusions drawn from these analyses of 

radiation effects are limited to the period of follow-up that commences roughly 19 years 

after exposure to radiation. Therefore these analyses may have excluded the period of 

risk of greatest relevance for radiation-induced lung cancer among survivors exposed at 

older adult ages. If, as is plausible, the induction/latency period for radiation-induced 

lung cancer among people exposed as older adults tends to be shorter than 19 years then 

this analysis would fail to capture a period of primary concern for radiation-induced lung 

cancer among adults exposed at older ages. 
David Richardson Page 5 2/28/2005 

Summary 

The epidemiological literature provides a very limited scientific basis for characterizing 

the joint effects of cigarette smoke and external exposure to ionizing radiation on lung 

cancer risk. The paper by Pierce et al. (2003) addresses an important question; however, 

interpretation of the findings of their analyses is constrained by the limitations outlined 

above. Crucially, their analyses only provide information on cases ascertained 

approximately two decades after the bombing and significant questions about the 

temporal aspects of the interaction between smoking and radiation are not addressed. 

One can speculate about characteristics of interactions between smoking and radiation on 

lung cancer risk by drawing upon evidence from analyses that have investigated smoking 

and radiation effects by fitting multistage models of carcinogenesis to epidemiological 

data. Although ionizing radiation has the general ability to produce mutational events, 

loss of certain functional capabilities at an early stage may increase the likelihood of 

radiation-induced later stage events. The pattern of increased risk of radiation-induced 

cancer with age at exposure (above age 20), and evidence of a linear dose response, has 

been the basis for positing that ionizing radiation exhibits primarily late-stage effects, 

although the large effect of childhood irradiation may also indicate an effect on an early 

stage of the carcinogenic process (Doll 1978; Schottenfeld and Fraumeni 1996; Peto 

2001). The patterns of lung cancer risk observed among smokers have been the basis for 

drawing inferences about the stage(s) of carcinogenesis affected by cigarette smoking. It 

has been posited that smoking affects an early stage of the carcinogenic process as well 

as a late stage (Brown and Chu 1987). To the extent that these exposures influence 

different stages of a multistage process of carcinogenesis the magnitude of their joint 

effects (and the distribution of induction/latency periods for induced cases) may depend 

upon their temporal ordering. 

 

Studies of underground uranium miners provide evidence about the joint effects of 

smoking and radiation exposure, although the mechanisms of interaction may differ for 

radon inhalation versus external radiation exposures. Recent analyses of lung cancer 

among American underground uranium miners by Archer et al. investigate differences in 

estimated latency periods by age at start of exposure and smoking status; the findings 

suggest that latency periods were typically longer for smokers than non-smokers and 

longer for those exposed at young ages when compared to those exposed at older ages 

(Archer, Coons et al. 2004). In contrast, Langholz et al found no significant evidence of 

differences in latency periods by smoking status in analyses of radon exposure and lung 

cancer mortality among Colorado Plateau uranium miners, but did find that radon effects 

peaked and declined much faster for those exposed at older ages than for those exposed at 

younger ages (Langholz, Thomas et al. 1999). Studies of radon exposure in the home and 

cigarette smoking have also examined the joint effects of these exposures; in a recent 

collaborative analysis, a model in which the combined effects of radon and smoking was 

additive was rejected (Darby, Hill et al. 2005). 

The assertion by Apostoaei et al. that the lung cancer model based on the analyses by 

Pierce et al. (2003) represents the current state of knowledge about radiation-induced 

lung cancer overstates the significance of that analysis of A-bomb survivor data. Rarely 
David Richardson Page 6 2/28/2005 

if ever does a single research paper establish the state of literature. The analyses by Pierce 

et al (2003) examine cancer incidence in a subcohort of approximately 44,000 A-bomb 

survivors who were alive and cancer free at the time of a smoking survey and provided 

responses that were logically-consistent. While interesting, the findings reported by 

Pierce et al. (2003) provide a weak basis for a meaningful scientific understanding of the 

joint effects of radiation and smoking on lung cancer risk. Neither those findings nor the 

other findings in the epidemiological literature provide compelling support for the 

conclusion that the smoking-radiation interaction is likely additive on the relative rate 

scale, as described by the current NIH-IREP model. Unfortunately, neither is there is 

there compelling evidence to support the NIOSH-IREP model. Rather, the nature of this 

interaction remains poorly characterized and the epidemiological literature provides an 

extremely limited scientific basis for this aspect of compensation decisions. A decision 

about how to model this interaction therefore becomes primarily a policy decision about 

how to make a compensation determination in the face of scientific uncertainty. The 

revisions to the NIH-IREP model with respect to age-dependency of lung cancer risk 

models in response to the analyses by Pierce et al. (2003) are questionable given the fact 

that analyses reported by Pierce et al. (2003) encompass relatively few A-bomb survivors 

who were exposed at older adult ages and include follow-up only for the period that 

commences roughly 19 years after exposure, therefore failing to characterize risk patterns 

during a potentially important risk period after radiation exposure. 

Conclusion 

The current epidemiological literature provides an inadequate basis for determining 

whether the current NIOSH-IREP or NIH-IREP model provides a more appropriate 

characterization of the joint effects of smoking and radiation dose on lung cancer risk. 

One alternative suggested by NIOSH is to run both models and use the result that 

provides the higher probability of causation. One might expect that appropriate 

specifications of uncertainty distributions around the parameters that differ for the two 

IREP models could produce similar results, however, the approach suggested by NIOSH 

would offer one method for accounting in a claimant-friendly manner for the substantial 

uncertainty about the smoking-radiation dose interaction. 

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Archer, V. E., T. Coons, et al. (2004). "Latency and the lung cancer epidemic among 

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Brown, C. C. and K. C. Chu (1987). "Use of multistage models to infer stage affected by 

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